40 results about "Maximum power point tracking algorithm" patented technology

The invention discloses an intelligent optical storage integrated AC / DC control method based on an energy management and control algorithm. The method comprises the following steps: acquiring and monitoring first data in real time; the working state of the photovoltaic module is dynamically adjusted through a maximum power point tracking algorithm, so that the photovoltaic module can output maximum power under various environmental conditions; according to the first data monitored in real time, the electric energy of photovoltaic power generation is dynamically distributed; acquiring a power grid fault state, switching an operation mode according to the power grid fault state, and controlling electric energy balance in the system; deploying an intelligent sensing system, collecting system operation state parameters in real time, and adjusting an energy management and power control strategy based on real-time data to enable the energy management and power control strategy to adapt to environment and load changes; monitoring faults and abnormal states, identifying fault types and positions, and intervening to recover normal operation of the system. The technical method for realizing optimal management and seamless operation switching of energy has the advantages of high system stability, high energy utilization efficiency and timely fault processing.

The invention discloses a photovoltaic grid-connected flexible control method and system, and relates to the technical field of photovoltaic grid-connected control, and the method comprises the steps: carrying out the fault prediction of a power grid through a power grid fault model, and automatically controlling a photovoltaic inverter to stop outputting power to the power grid when the power grid is predicted to have a fault risk, the method comprises the following steps: switching a photovoltaic system into an island mode, independently supplying power to a local load after the photovoltaic system is switched into the island mode, cutting off power supply of a power grid to the local load while the photovoltaic system independently supplies power to the local load, and adjusting the working state of a photovoltaic panel through a maximum power point tracking algorithm in the island mode. And a cooperative control strategy for the energy storage system is generated in combination with the operation state of the photovoltaic system and the local load demand. The control system can reasonably dispatch the charging and discharging process of the energy storage system according to the real-time load requirement and the power generation condition of the photovoltaic system, so that the stability and the energy utilization efficiency of the system are improved, and the power supply reliability in the island mode is ensured.

The invention provides a wind power high-voltage direct-current power transmission system, and belongs to the technical field of power transmission. The system comprises an intelligent wind driven generator, a modular converter station, an intelligent temperature monitoring direct current transmission line, a power grid friendly intelligent inverter station, and an intelligent regulation and control system integrating real-time data analysis, dynamic control and fault self-diagnosis. Through a maximum power point tracking algorithm and a self-adaptive control strategy, the system optimizes the wind energy conversion efficiency. The intelligent regulation and control system predicts wind power output by using a deep learning model and a random forest algorithm, dynamically adjusts voltage and current, and quickly responds to power grid demand changes. In addition, the system can quickly position and isolate faults, start a standby path and ensure continuous power supply. By adopting the wind power high-voltage direct-current power transmission system, the intelligent level of wind power high-voltage direct-current power transmission is improved, and the power transmission efficiency and the system stability are enhanced.

The invention relates to the technical field of wind-solar power generation hydrogen production, in particular to a wind-solar combined water electrolysis hydrogen production method and system.The method comprises the steps that output power data of wind power generation equipment and photovoltaic power generation equipment and input power data of an alkaline electrolytic bath are collected, and the collected data are preprocessed; respectively acquiring comprehensive adjustment coefficients of the wind power generation equipment and the photovoltaic power generation equipment; and determining the disturbance step length of the corresponding power generation equipment in the maximum power point tracking algorithm based on the perturbation and observation method at the current moment by using the comprehensive adjustment coefficient. The invention aims to dynamically adjust the disturbance step length, prevent the output power from wandering near the maximum power point to generate oscillation, and improve the stability and hydrogen production efficiency of a hydrogen production system.

The invention relates to the technical field of photovoltaic power generation, and discloses a photovoltaic power generation efficiency management intelligent optimization method, which comprises environmental data acquisition and illumination prediction, photovoltaic panel angle intelligent optimization, temperature adjustment and heat dissipation optimization and maximum power point tracking. Firstly, environment data are collected, and the illumination intensity at the next moment is predicted through an illumination prediction function; then, based on the predicted illumination intensity, the angle of the photovoltaic panel is optimized through an intelligent algorithm to minimize the illumination error. Thirdly, designing a temperature change and cooling power regulation function, optimizing a photovoltaic panel heat dissipation system, and ensuring that the temperature is within the optimal working range; and finally, the input voltage, current and power information of the inverter are utilized, and the input voltage of the inverter is adjusted in real time through a maximum power point tracking algorithm, so that optimal power output is realized. According to the method, the efficiency and the stability of the photovoltaic power generation system are comprehensively improved through environment data analysis and an intelligent optimization technology.

The invention relates to the technical field of solar lighting, and discloses an LED outdoor landscape lamp control system based on solar power supply. The system comprises a solar power supply management module, an energy storage scheduling and state management module, an intelligent sensing and environment identification module, a light control decision module and a self-adaptive feedback and system optimization module. The method comprises the following steps: acquiring voltage, current and irradiance data of a solar module, and combining a maximum power point tracking algorithm to generate power supply data; outputting scheduling parameters based on the dynamic scheduling model, acquiring environment data by using a multi-modal sensor and an image recognition technology, and calculating an illumination control factor; fusing the scheduling parameter, the illumination factor and the time factor, and calculating a target control matrix; and monitoring an execution feedback signal, and iteratively optimizing the control model based on historical control effect data to realize closed-loop optimization control. According to the invention, multi-source data fusion and adaptive control are realized, and the energy efficiency and intelligent level of the LED landscape lamp in a complex environment are improved.

The invention provides a photovoltaic cell maximum power point tracking method based on an improved sparrow search algorithm, relates to the technical field of photovoltaic power generation, and solves the problems that a traditional photovoltaic cell maximum power point tracking algorithm still falls into a local extreme value in a local shadow environment, so that the tracking precision is sharply reduced, and the tracking time is shortened. And the problem of failure in a local shadow environment is solved. According to the technical scheme, the method comprises the steps that a composite algorithm of an improved sparrow search algorithm and a variable step size perturbation and observation method is used as a control algorithm of an MPPT controller, iteration is conducted according to the flow of the improved sparrow search algorithm after the improved sparrow search algorithm is initialized at the initial stage of algorithm operation, and the output power of a photovoltaic cell array under the current duty ratio is calculated; the output power is the fitness value of the algorithm, and the global optimal position is updated. The method can adapt to a rapidly changing illumination environment, power oscillation is obviously reduced in the process of tracking the maximum power point, stable output of a photovoltaic cell can be guaranteed, and stable operation of a communication base station is guaranteed.

The invention discloses a light-hydrogen bilateral collaborative self-adaptive network construction control method, which is applied to a light-hydrogen bilateral coupling system, the system comprises a photovoltaic power generation unit and an electrolytic hydrogen production unit which are directly connected through an alternating current bus, the photovoltaic power generation unit comprises a photovoltaic panel, a DC / DC module and a DC / AC module, and the electrolytic hydrogen production unit comprises an AC / DC module, a DC / DC module and an electrolytic cell; the method adopts a maximum power point tracking algorithm and voltage threshold control to control a DC / DC module on a photovoltaic side, adopts voltage threshold control to control a DC / DC module on a hydrogen side, and adopts an alternating current droop control method introducing a phase control mechanism to control a DC / AC module or an AC / DC module. Therefore, the output frequency, the voltage and the phase of the corresponding photovoltaic power generation unit or the electrolytic hydrogen production unit are regulated and controlled, and dynamic power balance is ensured to be formed between the photovoltaic output and the electrolytic load. Two-way adjustment can be carried out, and stable operation of the system is ensured.

The invention discloses a four-switch Buck-Boost converter circuit for photovoltaic maximum power point tracking. The four-switch Buck-Boost converter circuit comprises a main circuit module, an input voltage detection module, an output voltage detection module, an output current detection module, a control output module and a driving amplification circuit module. The control output module comprises a micro-control unit, and the micro-control unit is provided with an ADC sampling interface and a PWM output interface. The main circuit module processes the input voltage of the photovoltaic panel and outputs direct current to charge the battery; the input voltage detection module, the output voltage detection module and the output current detection module are used for sampling the input voltage, the output voltage and the output current of the main circuit module and transmitting sampling values to the micro-control unit; the micro-control unit judges the mode of the main circuit module according to a sampling value, a PWM signal is output by the PWM output interface through an improved maximum power point tracking algorithm, and the on and off of a switching tube of the main circuit module are controlled through the driving amplification circuit module.

The invention relates to the technical field of power electronics, in particular to a rapid modeling method and system for a direct-current micro-grid converter, and the method comprises the steps: carrying out the harmonic component fitting of a switching function of a discontinuous converter based on the Fourier series in a triangular form, and generating a fitting switching model; according to the fitting switch model, obtaining a photovoltaic improved time domain model by using a maximum power point tracking algorithm; utilizing the fitting switch model to construct an energy storage improved time domain model; a bipolar switching function is defined according to the three-phase inverter circuit topology, and an inverter improved time domain model is obtained based on the bipolar switching function; and integrating the photovoltaic improved time-domain model, the energy storage improved time-domain model and the inverter improved time-domain model into a DC micro-grid architecture, and constructing an optical storage DC micro-grid joint simulation model. According to the method, the switching function of the discontinuous converter is fitted through the Fourier series based on the triangular form, so that rapid and accurate modeling of the DC micro-grid converter is realized, and technical support is provided for safe and stable operation of the micro-grid.

The invention relates to the technical field of photovoltaic cell MPPT, and discloses an intelligent tracking method, system and device for the maximum power point of a solar cell panel and a medium, and the method comprises the steps: obtaining a target data sample, and carrying out the analog-to-digital conversion of the target data sample; establishing a first maximum power point tracking algorithm, wherein an analog-to-digital conversion result is input data of the first maximum power point tracking algorithm; and performing intelligent tracking of the maximum power point of the solar cell panel according to the output of the first maximum power point tracking algorithm. The output voltage and output current analog signals of the solar cell panel can be accurately obtained in real time, the analog signals are converted into digital signals through analog-to-digital conversion, and an accurate data basis is provided for subsequent algorithm processing. Through the established first maximum power point tracking algorithm, the maximum power point of the solar cell panel can be quickly and intelligently determined and tracked, so that the power generation efficiency and stability of the solar cell panel are improved.

The invention discloses a circuit board optimization method applied to wind energy conversion, and the method comprises the steps: integrating a dynamic load matching module on a circuit board, collecting the voltage, current and frequency signals outputted by a wind turbine generator in real time, calculating the current wind energy conversion efficiency through an embedded controller, and combining with a preset maximum power point tracking algorithm, dynamically adjusting the switching frequency of the power semiconductor device; a layered heat dissipation structure is adopted, a circuit board base material is made of a high-thermal-conductivity composite ceramic material, a micro-channel cooling system is embedded in the circuit board base material, and the circuit board base material is connected with external heat dissipation fins through heat pipes; a thermoelectric refrigeration sheet is arranged below the power device, and the refrigeration power is dynamically adjusted according to the feedback of a temperature sensor, so that the temperature of a key device is maintained in a safe range of 50-80 DEG C; through a multi-objective optimization algorithm, the circuit loss, the heat dissipation efficiency and the electromagnetic compatibility are balanced, the circuit layout and the wiring path are optimized, and the influence of parasitic inductance and capacitance on the high-frequency switch is reduced.

The present invention provides a low-power RFID group scanning system based on energy collection and backscattering technology, which relates to the technical field of Internet of Things; the RFID tag in the system integrates a radio frequency receiving component, a photovoltaic component and a thermoelectric component, and is mainly used to collect radio frequency energy in the environment, and is supplemented by other energy sources, and energy conversion and storage are performed through a maximum power point tracking algorithm to ensure the stability of tag power supply; the RFID reader uses undersampling and sparse reconstruction technology to parse backscattered signals, and supports efficient identification and information extraction of multiple tags; the data management unit is responsible for storing and managing RFID tag information, and establishing a logical association between an optical fiber port and a pigtail; the system has efficient energy utilization capability, intelligent signal processing and a highly adaptable dynamic adjustment mechanism, and is widely applicable to optical fiber network management and low-power Internet of Things application scenarios.

According to the constant-voltage output electric ship photovoltaic power supply system based on the perturbation observation method, a photovoltaic input system comprises a photovoltaic cell module, a power converter module and a power control module; the DC boost system comprises a boost converter module and a boost control module. The energy storage system comprises an energy storage bin, a bidirectional direct-current converter module and a circuit breaker module. The power control module controls the power converter module through a maximum power point search algorithm, so that the output power of the photovoltaic cell module is maximum, and meanwhile, stable voltage output exists; the boost converter module controls the turn-on time and the turn-off time of a switch tube by changing the duty ratio of a PWM modulation signal, so that the input voltage is boosted to a higher output voltage level. According to the system, the maximum power point tracking algorithm based on the perturbation observation method is adopted to ensure that the photovoltaic cell is in the maximum power output state, and meanwhile, the output voltage is adjusted through the DC-DC converter to keep stable constant voltage output, so that the requirement of the electric ship for power stability is met.

The invention discloses a method for realizing maximum power point tracking of parallel photovoltaic modules in the technical field of photovoltaic power generation. The method comprises the following steps: step 1) carrying out data acquisition on a parallel circuit of a plurality of photovoltaic modules; 2) conditioning the data into an AD sampling signal, and sending the AD sampling signal to an AD port of a digital control chip to obtain a corresponding digital quantity; 3) processing by using a parallel photovoltaic module maximum power point tracking algorithm, performing maximum power point tracking on each photovoltaic module, and adding to obtain a grid-connected current given value or a grid-connected power given value in a power grid period; and step 4) sending the grid-connected current set value or the grid-connected power set value in a power grid period to a grid-connected controller to form grid-connected current. According to the photovoltaic module maximum power point tracking method, each photovoltaic module can realize maximum power point tracking.

The invention provides a photovoltaic heating system and a control method thereof. The invention relates to the field of photovoltaic technology. A photovoltaic heating system comprises a photovoltaic assembly, a resistor unit, a first switch and a controller. The resistor unit and the first switch are connected in series and then are connected between the positive electrode output end and the negative electrode output end of the photovoltaic module. The controller is connected with the control end of the first switch; the controller is used for determining the reference resistance of the resistance unit based on a maximum power point tracking (MPPT) algorithm when the photovoltaic module works at the maximum power point; and determining a control signal for controlling the duty ratio of the first switch based on the reference resistor, and outputting the control signal to the first switch. By controlling the duty ratio of the first switch, the equivalent resistance of the resistor unit connected in series with the first switch is adjusted, so that the photovoltaic module can operate at the maximum power point, the power loss of the photovoltaic module is reduced, and the effect of reducing energy waste is achieved.

The application relates to the technical field of power supply and distribution, in particular to an output power dynamic adjustment method for photovoltaic power generation grid-connected control, which comprises the following steps: obtaining a variation degree coefficient of a load adjustment step length at a current disturbance moment; obtaining a coincidence degree of the output power being a local peak value at the current disturbance moment according to the variation degree coefficient of the load adjustment step length; obtaining an optimized reduction degree coefficient of the load adjustment step length at the current disturbance moment according to the coincidence degree of the output power being the local peak value at the current disturbance moment; obtaining an optimized load adjustment step length and an optimized disturbance interval at the current disturbance moment according to the optimized reduction degree coefficient of the load adjustment step length; and adjusting the maximum power point load of a photovoltaic system by using the optimized load adjustment step length and the optimized disturbance interval at the current disturbance moment based on a maximum power point tracking algorithm, so that the problems of unstable output power and decreased power generation efficiency of a photovoltaic power generation system in a traditional algorithm can be solved.

The invention discloses an optical storage and charging integrated system based on reinforcement learning and a power distribution control method, relates to the technical field of optical storage and charging, and solves the technical problem that dynamic response speed, operation stability and energy management efficiency are difficult to consider under complex working conditions. The method comprises the following steps: determining a maximum power point of a photovoltaic power generation unit based on a maximum power point tracking (MPPT) algorithm to output electric energy; the reinforcement learning power compensation agent collects a plurality of working parameters in real time, calculates a power deviation between total output power and reference power, carries out proportional processing, and jointly inputs a state vector; obtaining a power compensation deep neural network based on the plurality of input state vectors and the multi-target weighted comprehensive reward function; and performing reasoning processing based on the real-time working parameters and the power compensation deep neural network to obtain the power regulation quantity of the energy storage unit, and entering a preset working mode. According to the invention, flexible, accurate and safe distribution of power among photovoltaic power, energy storage power and a power grid is realized.

The invention provides a low-power-consumption RFID group scanning system based on an energy collection and backscattering technology, and relates to the technical field of Internet of Things. The RFID tag in the system integrates a radio frequency receiving assembly, a photovoltaic assembly and a thermoelectric assembly, is mainly used for collecting radio frequency energy in the environment, is assisted by other energy sources, and performs energy conversion and storage through a maximum power point tracking algorithm to ensure the stability of tag power supply; the RFID reader-writer analyzes the backscattering signal by using an undersampling and sparse reconstruction technology, and supports efficient identification and information extraction of multiple tags; the data management unit is responsible for storing and managing RFID tag information and establishing logic association between an optical fiber port and a tail fiber; the system has efficient energy utilization capability, intelligent signal processing and a dynamic adjustment mechanism with strong adaptability, and is widely applicable to optical fiber network management and low-power consumption Internet of Things application scenarios.

The embodiment of the invention discloses a maximum power point tracking method, a photovoltaic system, a storage medium and a program product. The method comprises the steps that a first current and voltage curve obtained through forward scanning of a photovoltaic module and a second current and voltage curve obtained through reverse scanning of the photovoltaic module are obtained; determining a plurality of voltage intervals based on the first current-voltage curve and the second current-voltage curve; determining key parameters of a maximum power point tracking algorithm corresponding to each voltage interval; the key parameters at least comprise one or more of disturbance compensation, a power threshold value and waiting duration; the waiting time length is the waiting time length for acquiring power after the photovoltaic module is disturbed; and determining the maximum output power of the photovoltaic module based on the key parameters corresponding to each voltage interval and a maximum power point tracking algorithm.

The invention discloses an intelligent control method of a photovoltaic grid-connected inverter, which relates to the technical field of photovoltaic power generation and comprises the following steps of: checking a system, tracking a maximum power point, measuring output voltage and current of a photovoltaic array in a photovoltaic system in real time, obtaining delta P (K) by using an incremental algorithm, obtaining Pmax (K) by using a maximum power point tracking algorithm according to the delta P (K), and performing grid-connected control. After the inverter is subjected to grid connection, intelligent power adjustment and grid connection, the output of the inverter is adjusted through a power optimization algorithm to be close to a theoretical maximum power point and safety maintenance measures, the power increment is calculated in real time through an increment algorithm, and the maximum power point is updated based on the increment algorithm, so that the accuracy of tracking the maximum power point is improved; according to the method, the photovoltaic system can run close to the maximum power point, and the output of the inverter is adjusted through a power optimization algorithm, so that the inverter is close to the theoretical maximum power point, real-time optimization is realized, and the overall performance and the working efficiency of the photovoltaic system are improved.

The utility model discloses grid-connected and off-grid optical storage and charging equipment, which is used for supplying power to a load and comprises a photovoltaic module, an energy storage system, an inverter module and a control unit, solar energy is converted into direct current to be output based on the photovoltaic module; storing or releasing electric energy based on the energy storage system; one end of the inverter module is connected with the photovoltaic module and the power grid; the other end of the inverter module is connected with the energy storage system; the conversion between direct current and alternating current is realized based on the inverter module, and the inverter module maintains the maximum power output based on a maximum power point tracking algorithm; the control unit is connected with the energy storage system and receives working parameters of the energy storage system; the other end of the control unit is connected with the inverter module and the photovoltaic module, and the control unit controls the working states of the inverter module and the photovoltaic module based on the obtained working parameters of the energy storage system. By integrating photovoltaic power generation and energy storage technologies, the stability and reliability of power supply are enhanced.

A system for mitigating neutral point voltage fluctuations in an inverter circuit comprises an adder circuit 3c to receive first and second input signals and provide a first output signal. A subtracto

The invention relates to an intelligent speed regulation and control method and system for a solar generator, and relates to the field of solar power generation technologies. When the external illumination intensity is greater than the preset effective power generation intensity, determining an effective power generation position according to a preset sun motion algorithm, and controlling the generator to rotate to the effective power generation position; after the generator rotates, determining required reference voltage and theoretical generated power according to a preset maximum power point tracking algorithm; determining an equipment operation rotating speed corresponding to the required reference voltage according to a preset rotating speed matching relation, controlling a generator to operate at the equipment operation rotating speed, and obtaining actual power generation power in the operation process; and calculating according to the theoretical generated power and the actual generated power to determine a power error ratio, and outputting an alarm signal when the power error ratio is greater than a preset allowable error ratio. The solar generator has the function of improving the overall use effect of the solar generator.

The application provides a control method, system, device and storage medium for a hydraulic generator, and belongs to the technical field of wave energy generation, the method comprising: acquiring real-time operation data of the hydraulic generator, inputting a power generation power optimization model in combination with a preset water power coefficient to obtain ideal wave energy power generation power; obtaining actual output power of the generator through a maximum power point tracking algorithm; determining a working condition according to the real-time data and the actual output power: if it is a continuous power generation mode, generating a smaller first control angle instruction to make the hydraulic generator continuously generate power; if it is an intermittent power generation mode, generating a larger second control angle instruction to make the hydraulic generator intermittently generate power. The control method, system, device and storage medium for the hydraulic generator provided by the application generate corresponding control angle instructions for different power generation modes, thereby effectively adjusting the output voltage of the hydraulic generator to adapt to the change of wave energy, and improving the power generation stability and equipment operation safety.

The application discloses a kind of based on reinforcement learning's light storage fills integrated system and power distribution control method, it is related to light storage fills technical field, it is difficult to take into account dynamic response speed, operating stability and energy management efficiency under complex working condition technical problem.The method comprises: based on maximum power point tracking MPPT algorithm determines the maximum power point of photovoltaic power generation unit for electric energy output;Real-time acquisition is carried out to multiple operating parameters by reinforcement learning power compensation agent, the power deviation between total output power and reference power is calculated, and proportioning treatment is carried out, and state vector is inputted jointly;Based on multiple input state vectors, multiple target weighted comprehensive reward function, obtain power compensation deep neural network;Based on real-time operating parameter, power compensation deep neural network carries out inference processing, obtains the power regulation amount of energy storage unit, enters preset working mode.The application realizes the flexible, accurate and safe distribution of power between photovoltaic, energy storage and power grid.

The invention relates to the technical field of power supply and distribution, in particular to a photovoltaic power generation grid-connected control-oriented output power dynamic adjustment method, which comprises the following steps of: acquiring a change degree coefficient of a load adjustment step length at a current disturbance moment; according to the change degree coefficient of the load adjustment step length, obtaining the conformity that the output power at the current disturbance moment is a local peak value; according to the conformity that the output power at the current disturbance moment is a local peak value, obtaining an optimization reduction degree coefficient of the load adjustment step length at the current disturbance moment; obtaining an optimized load adjustment step length and an optimized disturbance interval at the current disturbance moment according to the optimized reduction degree coefficient of the load adjustment step length; based on the maximum power point tracking algorithm, the optimal load adjustment step length and the optimal disturbance interval at the current disturbance moment are adopted, the maximum power point load of the photovoltaic system is adjusted, and the problems that the output power of a photovoltaic power generation system of a traditional algorithm is unstable, and the power generation efficiency is reduced can be solved.

The present application relates to the technical field of wind and solar power generation and hydrogen production technology, and specifically to a wind and solar combined water electrolysis hydrogen production method and system, the method comprising: collecting output power data of wind power generation equipment and photovoltaic power generation equipment and input power data of alkaline electrolyzers, and preprocessing the collected data; obtaining comprehensive adjustment coefficients of wind power generation equipment and photovoltaic power generation equipment respectively; and using the comprehensive adjustment coefficients to determine the perturbation step size of the maximum power point tracking algorithm based on the perturbation observation method for the corresponding power generation equipment at the current moment. The present application aims to dynamically adjust the perturbation step size to avoid oscillation of the output power hovering near the maximum power point, thereby improving the stability and efficiency of the hydrogen production system.

The invention discloses a maximum power point tracking algorithm circuit for piezoelectric energy collection, which is characterized in that the output end of a piezoelectric energy source is connected with the first signal input end and the second signal input end of a rectifier, and the output end of the rectifier is connected with the input ends of a rectifier conduction time duty ratio detection circuit and a buck-boost impedance matching converter; the output end of the rectifier conduction time duty ratio detection circuit is connected with the input end of the interval approximation algorithm circuit module, the output end of the interval approximation algorithm circuit module is connected with the control end of the buck-boost impedance matching converter, and the input end of the energy storage module is connected with the output end of the buck-boost impedance matching converter. According to the circuit, whether the output of the voltage power supply is at the maximum power point can be judged by judging whether the conduction duty ratio of the rectifier reaches 50%, and the impedance matching circuit is controlled to track the maximum power point through an interval search algorithm.

The present invention relates to the technical field of power energy storage dispatching. A high-efficiency and high-reliability power conversion control method for photovoltaic power generation provided by the present invention monitors the environment and equipment status of a photovoltaic power station in real time, and uses an environmental monitoring and early warning model, a maximum power point tracking algorithm, and a power generation power calculation model to dynamically adjust equipment parameters to ensure that photovoltaic cells operate at the maximum power point. If the actual power does not match the expectation, a genetic algorithm is used to optimize the power generation power calculation model and correct the control commands of the photovoltaic power station equipment. The present invention solves the problems of the stability and reliability of the power conversion system in extreme environments, improves the energy conversion efficiency, reduces the operation and maintenance costs and failure rates, and realizes the efficient and stable operation of the photovoltaic power station.